class_docstr: Quantizer for handling weights in Conv2D/DepthwiseConv2D layers.
code: def build(self, tensor_shape, name, layer):
      min_weight = layer.add_weight(
          name + "_min",
          shape=(tensor_shape[-1],),
          initializer=tf.keras.initializers.Constant(-6.0),
          trainable=False,
      )
      max_weight = layer.add_weight(
          name + "_max",
          shape=(tensor_shape[-1],),
          initializer=tf.keras.initializers.Constant(6.0),
          trainable=False,
      )
  
      return {"min_var": min_weight, "max_var": max_weight}
  
file_path: model-optimization/tensorflow_model_optimization/python/core/quantization/keras/experimental/default_n_bit/default_n_bit_quantizers.py
imports: import tensorflow
  from tensorflow_model_optimization.python.core.quantization.keras import quantizers
label_desc: Use image node_id 2 for calling the DefaultNBitConvWeightsQuantizer obj's underlying member method code with example usage: obj.build(tensor_shape, name, layer) and returns: dict